docs: def remove_masked_labels(self, mask, partial_overlap=True,
                               relabel=False):
          """
          Remove labeled segments located within a masked region.
  
          Parameters
          ----------
          mask : array_like (bool)
              A boolean mask, with the same shape as the segmentation
              image, where `True` values indicate masked pixels.
  
          partial_overlap : bool, optional
              If this is set to `True` (default), a segment that partially
              extends into a masked region will also be removed.  Segments
              that are completely within a masked region are always
              removed.
  
          relabel : bool, optional
              If `True`, then the segmentation image will be relabeled
              such that the labels are in consecutive order starting from
              1.
  
          Examples
          --------
          >>> from photutils import SegmentationImage
          >>> segm = SegmentationImage([[1, 1, 0, 0, 4, 4],
          ...                           [0, 0, 0, 0, 0, 4],
          ...                           [0, 0, 3, 3, 0, 0],
          ...                           [7, 0, 0, 0, 0, 5],
          ...                           [7, 7, 0, 5, 5, 5],
          ...                           [7, 7, 0, 0, 5, 5]])
          >>> mask = np.zeros_like(segm.data, dtype=np.bool)
          >>> mask[0, :] = True    # mask the first row
          >>> segm.remove_masked_labels(mask)
          >>> segm.data
          array([[0, 0, 0, 0, 0, 0],
                 [0, 0, 0, 0, 0, 0],
                 [0, 0, 3, 3, 0, 0],
                 [7, 0, 0, 0, 0, 5],
                 [7, 7, 0, 5, 5, 5],
                 [7, 7, 0, 0, 5, 5]])
  
          >>> segm = SegmentationImage([[1, 1, 0, 0, 4, 4],
          ...                           [0, 0, 0, 0, 0, 4],
          ...                           [0, 0, 3, 3, 0, 0],
          ...                           [7, 0, 0, 0, 0, 5],
          ...                           [7, 7, 0, 5, 5, 5],
          ...                           [7, 7, 0, 0, 5, 5]])
          >>> segm.remove_masked_labels(mask, partial_overlap=False)
          >>> segm.data
          array([[0, 0, 0, 0, 4, 4],
                 [0, 0, 0, 0, 0, 4],
                 [0, 0, 3, 3, 0, 0],
                 [7, 0, 0, 0, 0, 5],
                 [7, 7, 0, 5, 5, 5],
                 [7, 7, 0, 0, 5, 5]])
          """
  
          if mask.shape != self.shape:
              raise ValueError('mask must have the same shape as the '
                               'segmentation image')
          remove_labels = self._get_labels(self.data[mask])
          if not partial_overlap:
              interior_labels = self._get_labels(self.data[~mask])
              remove_labels = list(set(remove_labels) - set(interior_labels))
          self.remove_labels(remove_labels, relabel=relabel)